基于小波熵的弹丸激波信号特征提取方法研究

The Study on Feature Extraction Methods of Projectile Shockwave Signal Based on Wavelet Entropy

在实验中获取的弹丸激波实测信号,由于受到激波在空气中传播时各种因素的影响,使得获取的信号有很多不确定性,其持续时间难以利用传统的信号处理方法来获取。文中从小波变换的角度出发,通过在尺度域上对信号能量的一种划分,引入了小波能谱与小波熵作为信号特征提取的特征量来反映系统信号的统计特征。实验结果表明,该算法能有效提取弹丸激波信号特征,速度快、准确率高,而且具有对噪声不敏感的优势。

Due to influence of a variety of factors in the air, the experimental projectile shockwave signals have a lot of uncertainties; its duration is difficult to obtain using traditional signal processing methods. Started from the wavelet transform, the signal energy was compartmentalized in the domain of scales in the paper, and the wavelet energy spectrum and entropy were introduced as the features to reflect the statistic character. The experimental results show that the method can effectively extract shockwave signal features. It＇s with the advantages of high speed, high accuracy and insensitive to noise.